Systems | Development | Analytics | API | Testing

Test automation is an essential component when it comes to delivering high-quality software. However a lot of QA teams face challenges when it comes to deciding which test cases they need to prioritize for automation. The selection process can be hard, especially if you consider the limited resources that these teams sometimes have and complexity of modern applications.

Between the relentless pressure to ship new features and updates, and the increasing adoption rates of DevOps, AI’s influence in the future of the testing landscape is palpable, and the focus in the coming years will be applying that to QA teams everywhere.

When evaluating automation testing companies, you’ll notice most promise the same benefits: faster release cycles, fewer bugs in production, and less testing work for your development team. But in our experience, many fall short. They bottleneck releases, miss bugs users immediately notice, and still rely on your developers to write and maintain tests.

Everyone is taking part in the AI scramble, some more successfully than others, as we all know. But many enterprise companies are still just getting their feet wet. Here at Qlik we saw an opportunity to try to capture what it is that these successful companies did to get value from AI for their organizations. So, we partnered with IDC to get those answers and discovered that preparation is a major difference maker for success with AI.

Data products in BigQuery help teams organize and share data effectively, by managing data as a product, cutting down time to insights.

Business intelligence (BI) dashboards, also known as BI dashboards, are a powerful way to help people collect, share and analyze their business data to make informed decisions. Business dashboard software can help users monitor operations, optimize processes, and improve overall business performance by having data readily available, and can also help detect and prevent potential problems before they become issues with its use of real time data.

Creating API documentation from scratch remains a complex and time-consuming challenge, especially as APIs become more central to digital transformation in 2025. Today’s best API documentation tools leverage automation, AI, and interactive features to simplify the process, ensuring documentation is clear, accessible, and up-to-date for both technical and non-technical users.

Designing a website that delivers a smooth user experience requires more than just visually appealing pages or functional interfaces. The key to an effective UX design lies in the understanding of how users interact with your site from the moment they land on a page to when they complete a desired action. This sequence of steps, better known as the "user flow," plays a critical role in determining whether visitors engage meaningfully or abandon the site out of confusion or frustration.

To ensure a seamless, student-centric experience, universities must use automated data integration to centralize information and enhance decision-making.

One of the most exciting additions to Rails 8 is undoubtedly Solid Queue, a new library for processing background jobs. You might not think it's that big of a deal. After all, there are plenty of other queuing systems out there. If you work with Rails, you'll likely know about Sidekiq and Resque — both are exceptionally performant and reliable. There is also GoodJob and the venerable DelayedJob. With all those options available, do we really need another queuing system? Let's find out together.